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引用次数: 0
摘要
摘要 针对局部电磁加载作业采集的信号通常混有背景噪声（尤其是白噪声）的问题，本文提出了一种基于交叉递推量化分析（CRQA）的电磁声发射信号去噪技术。首先，通过经验或优化算法设置变模分解的分解层和惩罚因子，然后对原始信号进行分解。其次，利用 CRQA 算法选取主要成分，通过叠加重构得到去噪后的电磁声发射信号。仿真和实验结果表明，当加入 5 dB 噪声时，与相关系数算法相比，CRQA 能有效去除电磁声发射信号中的背景噪声，有助于实现合金材料的高精度无损检测。
Investigating Electromagnetic Acoustic Emission Signals Denoising for Alloy Materials Nondestructive Testing: A CRQA Method
Aiming at the problem that signals collected from local electromagnetic loading operations are usually mixed with background noises (especially white noise), this paper proposed an electromagnetic acoustic emission signal denoising technology based on cross recurrence quantification analysis (CRQA). Firstly, the decomposition layer and penalty factor of variational mode decomposition are set by experience or optimization algorithm, and then the original signal is decomposed. Secondly, the main components are selected by the CRQA algorithm, and the electromagnetic acoustic emission signal after denoising is obtained by superposition reconstruction. The simulation and experimental results show that when 5 dB noise is added, CRQA can effectively remove the background noises in electromagnetic acoustic emission signals compared to the correlation coefficient algorithm, and it can assist in realizing the high-precision nondestructive testing of alloy materials.
期刊介绍：
Russian Journal of Nondestructive Testing, a translation of Defectoskopiya, is a publication of the Russian Academy of Sciences. This publication offers current Russian research on the theory and technology of nondestructive testing of materials and components. It describes laboratory and industrial investigations of devices and instrumentation and provides reviews of new equipment developed for series manufacture. Articles cover all physical methods of nondestructive testing, including magnetic and electrical; ultrasonic; X-ray and Y-ray; capillary; liquid (color luminescence), and radio (for materials of low conductivity).
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